More great RPA Use Cases for your business – #26


Due to big demand, we have recorded another RPA Use Cases episode. In this episode of the Process and Automation podcast Arno and Sascha speak about the most common use cases for RPA.

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Hello. And welcome back to another episode of the process in automation podcast was the automation guys in today’s episode, we will be looking at. RPA use cases. Recently, we had a couple of sessions about chat bot use cases, and we received, um, plenty of feedback. And this is why we are covering RPA use cases today.

So use cases seem to be very, um, very popular, um, because it applies to, to real business problems and where intelligent automation tools like RPA or process mining and chatbots can actually solve problems. And, let’s get started was a few, I think there are so many we could cover and we select selected just, uh, um, the list offers sort of very common, um, use cases.

What do you think will be sort of the number one or one of the number one use cases? Well, I think it’s, it’s hard such a to actually put one at the top. Um, of course, for our listeners, just as a refresher on RPA theory, um, of course, RPA can be used to automate repetitive tasks, you know, both in your, your back and your front office, where human intervention is required.

And, um, you know, and this is from kind of data entry type activities, data extraction. To invoice processing, batch processing. So I think it’s important to realize that RPA is, um, can be deployed across the business. And if we look at some of the. Common areas where we see strong use cases for RPA exists, that’s in processes like your quote to cash.

Every business has a quote to cash process, uh, in, in some sort of way. Um, even if they don’t know it, um, this is where you sell either a product or a service. And, uh, you know, what happens is that, um, you, you provide, uh, that service offering and there’s a lot of steps that happens in between.

Um, that’s kind of, um, related to providing a product or that service. Uh, and at the end of the day, when you deliver that, that’s when you obviously produce your revenue. Um, so, you know, we, we see quote to cash assistance. That’s a really important one. It’s, it’s kind of like a core use case for, for every business.

Um, and of course, automation. Um, with inside that process is really important, um, because that reduces the rate of manual errors, it provides, you know, provides you faster service to your customers because, you know, automation can speed up this process. Um, customers will for, for instance, receive their products, their services quicker, um, they’ll receive their invoices quicker and that would lead to sort of earlier payments and improve cash flow and overall reduce, you know, the, the, the errors.

Process which reduce your, your business costs, for example? Absolutely. So this is a, this is an important one. And, um, as we cover, um, uh, uh, in covering lots of these use cases, um, the more. The data you have in your business? I think the easier it is to automate those things. And in RPA you could say, um, yeah, it’s like, yeah, it’s your digital worker.

And, um, uh, you as a human worker, you look at the document, you can immediately identify patterns and structured data out of maybe a letter or invoice or, uh, um, some something else. Um, so in, in general, um, if your bot needs to. Do all that work we need to support, but these bots is digital workers. Um, if you can then convert unstructured data to structured data, then you can really, that automation, even more and that’s so, so important, uh, as well in the, in the other process.

So, quote two caches, you sending your invoices, you use any new quotes out to customers. Um, the other, the other very important one is your procuring stuff for you. To maybe produce things, um, and or you use received services from other companies sort of purchase, uh, procure to pay source, to pay process.

It’s a very, very important. And in some, some might think these processes are around for years. Um, all the problems around that process should be already tackled. Now, I think that’s, um, I think that’s that’s far from, from it, um, companies and we have also growing companies who are just starting to tackle, um, the, the procure to pay, uh, when you just think about our growing startup.

So maybe 10 years ago, or five years ago, they just had a few supplier invoices, but suddenly they become sort of a market leader in providing services and suddenly they. They have to procure a lot of stuff. Um, and they have to handle this influx of invoices, procured to pray really involves, um, extracting invoices and payment data from sort of, so model based systems like supplier emails.

So this is a very typical one. Email comes in, it will be maybe forwarded to manager to approve someone is approving it. And then it goes somewhere. It goes to the finance person. Uh, but I’m doing all that stuff manually. Um, going into the ERP system, CRM systems, going into the bank, into logistic systems to just collect all that data, which is related to procure to pay.

Um, yeah, so I think that’s, that’s, that’s very, very slow an error prone. Um, um, but I think that’s a, that’s where, where RPA comes in, it can sort of build that, that glue between all the systems can fill these integration gaps and yeah. And it it’s a, it’s a light touch. You don’t need any complex projects to get it done because it’s you mainly working on the front end.

Uh, it can provide that, that easy way to. To do that automation without involving too much, uh, developers, et cetera. So you extracting data from invoices, um, intelligent document processing. Um, I think that kind of stuff, um, is super simple. Yeah, absolutely. And I think, you know, um, this is cash leaving your business.

So you want to have a really good handle on that. And you want to have a kind of single source of truth. All of these transactions, you want to be able to, to look into those and make sure that those transactions are really robust, but as automated as possible possible with the bright sort of governance around it.

Um, without throwing too much people. To it, um, to do manual processing. And the third one we want to look at, um, without, with sort of, um, uh, receiving money, paying out money in your business. And of course the third one is all to do with customer onboarding. So, you know, mostly. Businesses do have, uh, a customer onboarding process.

That’s, that’s really critical to get right and get those customers on board to make sure that the products and services, um, can, can, you know, it can be offered very quickly to them. And you know, these days you can use a very sophisticated. Uh, OCR and cognitive automation, um, you know, to, to automate the, the customer onboarding, uh, activities.

And, you know, some of these things can, can, can be done instantaneously where you, um, even have got legacy systems in, in the background when you plug in those, those, those, those right automation technologies in front of it, then your, your customer onboarding. Um, journey can be really, really lean. It can be very fast.

Um, in a, in one study, we, we see, um, uh, done earlier this year and it was done by work fusion. Um, this was for a major bank and, you know, their customer onboarding process. Um, reduced from 20 days to only five minutes, because what they did is they, they, they used all of their legacy systems, but they plugged in all of this progressive automation tech in front of it, including RPA to absolutely drastically reduce that onboarding journey.

You know, from, from weeks to two minutes, you know, which is incredible, you know, and, and I think that is the kind of expectation and the benchmark, um, you know, out there for, for these types of processes. And I think, you know, in, in, in a day we Lyft Lyft today and with, um, kind of customer retention and customer satisfaction being, um, such an important thing.

It is in my view as sort of a no brainer in terms of. Yeah, very often. These use case, you just mentioned the, the 20 days to five minutes and very often union here. Um, yeah. Um, all those programs are only there for, for reducing FTEs within businesses. And the very often that’s, that’s, that’s what you see in our calculators.

Isn’t it? So how many FTEs you might save? Um, but we, we both are really strong believers that. These initiatives or these technologies, shouldn’t be it shouldn’t be focused on, um, reducing, um, uh, FTEs. Um, let’s just really, um, offloading this, this mundane and repetitive work, isn’t it from, from your FTEs.

And then, um, because businesses generally have the desire to grow, to use the, sort of the freedom free, freed up time to, to, to grow the business where and use you use the manpower. The human part are really on the, on the, on the, on top. Just to humans or humans do best. So sometimes you read these very impressive figures.

Um, yeah, you save FTEs, but you, you probably would better describe it. Like you, you free up time for 67 FTEs to do something else. Sometimes I, I think, um, some of the statistics are a bit negative. You read so. The results are impressive. Um, uh, if you’re a major company and you can reduce it from 20 minutes to 20 days to five minutes.

Um, but, um, yeah, it should be all about how can you reduce your sort of capacity in the business that are not already used to improve your capacity? Yeah. Was, was who was your workforce?

Uh, so yeah, the other really common, common areas and business functions, um, we look at, um, uh, is, um, data migration and data entry. So, um, so we, we know this all their legacy systems. Um, I think they’re probably not real big enterprise out. There was legacy systems, uh, But in these systems perform critical functions at companies.

And if you even at bang stairs, they’re all COBOL systems and all terminal systems still available. Um, and they do some, some of the critical number crunching. So billing systems, um, say all that stuff, um, Yeah, can’t be really pulled out sort of, um, whereas was API APIs in a modern sense and in a modern world, you have a nice API.

Um, but if you can’t really get to it, you need to find other ways. Um, and the, the old way was, uh, maybe exporting a CSV file or, um, exporting data really, really difficult. Um, uh, just copying it manually from one system to another and was RPA. You can, you can now. Really use, um, uh, oh, you can use RPA for, for going into these old legacy system.

The digital worker do that work. Um, and, uh, yeah. And you can, um, transfer that style, uh, that data out error free and you can do it all year round. No one has to work in the basement somewhere where there’s all terminal belongs. Yeah, you can get that data out really, really, really reliable. And, um, and then you take that data and you maybe update this into other more modern systems, you have forum, um, and that there could be hundreds of different systems you need to update regularly.

Um, and, uh, yeah, RPA can then go like. Lots of firearms going into this different systems and, um, just making these changes. Um, uh, so sometimes, yeah, so you might forget even about your legacy systems because you put this very powerful glue in between, uh, at some point, this is. Well, we will be migrated and there will be proper API APIs.

And then you need to look at other, other things, how we connect this, then you look probably at integrated, uh, integration platform as a service. But until then, RPA is, this is a good friend. Um, and to, to get these use cases, Yeah. And you, you speak about sort of data migration and data entry into various system, but I also think another really, really good use case for RPA is in that sort of data maintenance space where, you know, you, you, you might have various departments in, in your business, including HR, customer service and marketing.

And, you know, they, they need to routinely update data and this is data spanning your customers, let’s say personnel data. And this is data that that’s constantly changing. And, you know, you could set up RPA bots that, you know, automatically update those, those relevant data from either inbound emails you received from customers, um, or, um, you know, online forms, whatever that source of update is, and really to ensure that all of those system.

It’s the systems used by these departments, uh, accesses that single source of truth and not that kind of error free data, which would just the latest data and also data validation. Data validation is really important because, you know, we, um, from a traditional perspective, a lot of the sort of data validation routines are embedded within in databases.

Um, so what we want to do, um, is we want to kind of check data. Again, sort of publicly available data sources to make sure that if that data is still current and, um, you know, RPA as a very, very good tool to do so where, you know, you can try and just tool to go to various other data sources, including sort of, uh, online data sources where it kind of scrapes data from websites and make sure that.

Data you’ve got is still valid and go update your, your, your sources of truth in, in, in, in your, in your backend, for example. And also, you know, if you have inbound data where you have to extract data from PDFs, um, scan documents, and, and you know, any other types of forms, including sort of Excel spreadsheets, and you could, you could use, um, RPA really.

Extract that data, um, you know, uh, use pattern recognition, for example, um, when you look at that data and, uh, when you’re going to need to go key that data into, um, other systems, you know, you could use, um, sort of machine learning, uh, algorithms to make sure that these, this data is valid. Um, and, um, you know, you could at, at, at lightening speed really.

Uh, from extraction to transformation, to loading very quickly, uh, um, get that data into, into your business and to organization and also maintain it. So, so again, just around this sort of data extraction data validation, updates. You know, uh, bots or RPA bots are really, really useful in doing so. And of course, you know, they can do this 24 7, um, without any errors.

So, so a very, very, very useful use case for, for RPA. Yeah, I think, um, the, you know, you mentioned, uh, customer satisfaction, uh, a couple of times. And um, if you think about, um, um, maybe insurance claims again and insurance contracts and all that stuff and general legal documents sometimes, uh, if there would be a claim or some, some, uh, some event where someone needs to go through all this huge amount of data or these documents before.

It is not, it doesn’t really make sense anymore that, that a human is going through thousands of pages or just an army of people going through thousands of pages of documents. So the was RPA and was the relevant, um, connected systems like OCR, that kind of stuff. You could, you could have your digital worker going through a document to document finding relevant information and getting through.

The claims processing medical, documentations doc doctor’s statements or whatever in, in sort of no time. And then it might be presented to some other, uh, to maybe to human, to, to verify lots of things, but that, that whole process then. So, so you do, and you can maybe pay out. To a critical ill patient much earlier.

Um, so yeah, so that there will be customer satisfaction. You could really do, do, do have a big, yeah. You have a big impact. Um, so yeah, those kinds of scenarios are, uh, out there. Um, and wait for four being, being processed. Uh, I think, um, I think more than, uh, more than 50% of businesses are already thinking about doing RPI and probably doing early things of RPI.

But if you think about the other 50%, just globally on companies who are not tapped to who have not tapped into that opportunity, they can, yeah. They can use these use cases to, to look at, um, to get started with. Um, there’s more, I think there’s, there’s, there’s more like, uh, like, um, like reports, I think.

Um, oh, stay, there are people in businesses that they’re doing reports at the end of the week, at the end of the day, or very often and end of the month. So very typical month-end reports. And then usually what happens is, um, you copy data from one spreadsheet and other system is producing another spreadsheet and then someone is creating a nice.

XR macro and smooching information together. And that can take him a couple of people in the business, a couple of hours per, per, per week, per months. And, um, and this is not something. We should do, we should do manually. So these reports, the report compilations, they also based on very strict rules. And this is a, it’s a great area where digital workers can, can take over when it’s rules based, you can replicate it easily.

Um, and, um, you know, your digital worker can just do these reports and merge them. The data together, hundreds of spreadsheets, if, if that is the case and, um, it will be done, um, do the analog, uh, analytics, maybe behind it and another tool and produces the output in, um, without errors and on time. Yeah. And you have the, the time back, um, for your, for your, for your team.

Yeah, absolutely. And I think reporting mass generation of management information, um, you can also train your bots to obviously react to a specific issues that’s highlighted with inside the report. You know, so if there is some alerts that, um, you’re trying to bots to pick up on, then those reports can actually be very valuable to.

Um, draw somebody’s attention to the fact that there’s something specific in the report that needs, um, somebodies attention. Um, you know, whether or not there’s a critical issue with, uh, the provisioning of services. For example, you can actually train the bot to not just generate those reports, but also actually to, to react to something that’s within sight a report and get the right people involved.

Um, to, to be able to solve this issue. Um, you know, and also, uh, let’s just look at communication, uh, since we talking about it, um, it’s not just about creating and sending this report, but if you have got any requirement to generate mass emails, um, where you have to rely on. Data from multiple systems, um, to be sourced and, um, to produce these emails, to, to be sent out to, uh, potentially clients or prospects at the unit, depending on what you want to use mass emailing for.

Um, it’s a, it’s a very easy task to do that with RPA because you can actually source that data from very disparate sources. Uh, and if you send these emails frequently, um, you know, this is a perfect use case to, to actually. Uh, automate that, that process, you know, and it kind of brings me to activities within sight, um, you know, commercial functions, including sales and marketing.

Um, you can automate something like lead nurturing, where leads arrive from various channels, including. You know, uh, lead collection forms on the website from vendors, emails, LinkedIn, and all of that can go into your automated lead, nurturing RPA process. Um, if you look at sales, um, of course, you know, uh, we want salespeople to focus on building relationships and selling.

Um, but a lot of their times is spent on operational activities. In, in most organizations. So, so with inside your, your sales function, um, you could automate those operational activities out of the picture and allow yourselves people to, to focus more on selling Rodan and the administrative, but, you know, burdens that, that, that comes with with the, uh, the day to day job of, of, of selling, for example, Absolutely.

And on that, that specific areas, um, um, or these specific areas in, in sales functions could be creating, um, the invoices. So as part of the sales process, at some point you have to send out an email, it was an invoice, or even send a letter these days. But even that could be handled by, by, by a bot. Um, yeah, I think, uh, Th the, the key thing is that the bot will, will help the salesperson, um, collecting all that data and, um, making sure that data exists correctly in the CRM system and in the finance system, accounting system and, uh, someone, maybe the sales person only typing that stuff into the CRM.

And for some reason, on a Friday afternoon, I might forget to press a button or do some thing. Uh, it might not transfer properly. So. So the, the bot can make sure it’s always run consistent, um, CRM data, um, accounting data is all up to date and, um, and, and then invoices are sent out automatically. I think that’s, um, a thing is an easy one.

Usually sales, salespeople. They don’t like all that admin stuff. Like you mentioned before sales people are good, usually in selling and not with this admin stuff. We, we all demand. Uh, I think as business owners that they do all that stuff, but if we can help them with support, I think they will be very, uh, thankful.

Um, and, and that as well as updating the CRM in general, uh, it is time consuming. Sure. Sometimes they have to enter very specific information, um, uh, in to just track what’s going on. Was this, uh, was this customer, but it’s generally very time consuming, unproductive time for them. And. Yeah, so. So, this is a way where they can support the, um, the, the sales agent and the sense people to, to collect all that information and to make sure it is all updated in a right, right places.

Um, and, um, and sometimes even. The, the sales agent doesn’t need to go into the CRM system so that the bot can take, take care of, of, of stuff from, from outside, maybe getting information from other systems. Um, but this is, uh, yeah, one, one very big area in, in sales. And, um, um, and if, if the system is not right, uh, it produces all sorts of errors, um, uh, which is not helpful for the business.

And, um, if we can get an error or free. Yeah. Everyone benefits from this one. Yeah. True. Yeah. I mean, it’s interesting that you mentioned the kind of the hand handover between the Salesforce, um, that actually looks after kind of selling and then also from a accounting perspective, which, um, does the billing, um, we, we do see there are gaps out there in, in some of the use cases we see.

Um, where does that kind of have that smooth handover from your customer relationship management system to your accounting system? Um, yeah. Like I say, gaps in that process and RPA is a perfect place to, to, um, sort of fill those gaps and really make sure that the transition between, um, you know, your, your sales cycle to, to, to your billing cycle is as really as smooth as it can be.

And of course, you know, you talked about Sasha about updating CRM. Um, making sure that, you know, your CRM is updated with all your customer interactions. Of course, you know, there’s a wealth of use cases that you can deploy RPA with that it gets all of those, um, different sources of information that pertains to customer interactions and go and update your CRM.

So that, that information is visible to the rest of the, the business, you know, and, and in terms of. On this track of keeping, um, data updated. Um, you know, sometimes, you know, there, there is a lack of integration between HR and CRM systems and, uh, you know, RPA bots can actually ensure that, you know, CRM changes are, are, are uploaded, um, you know, to, to, to, to kind of like the scorecards.

The, the sales reps use so that they can see their progress in real time. Um, so, you know, so that, that’s a really important use case as well. Um, you know, and it all kind of just boils down again to the fact that, you know, people want to see up-to-date information. Um, when we talk about customer relationship management, um, you know, we all rely on, on, on, on, on, on, on our sort of good data points.

Um, that comes from a variety of different systems that we need to, to ensure that our customers are happy. And you know, of course, RPA is as a, as a, as a very, very good tool to be able to source that information and keep it up to date. Um, so it is available. It gives you a very good picture of, um, you know, your, your customer record.

Um, we always call it quality 360 review, um, you know, whatever you call it, know your customer. All of that information is really important. Um, so, so that, that, that everybody has got the information at their fingertips. If they do engage with our customers, um, you know, uh, it, it does feel like from a customer engagement perspective, we know our customer, we know what to sell them.

We know the history with us. Um, so again, very, very important. Yeah, definitely. The, um, this is one, one important area. Um, We have to make our customers happy. Um, but at the same time, we have to look as well at, uh, sort of, um, some of the other departments and one very important department, which comes up in our conversations and, uh, is, is a thing.

Sort of waking up more and more was HR automation. So the HR departments, um, how could, how could we sort to sort out the problems for them? I think a big one in HR is, um, is this candidate sourcing, you know, so, so the whole, the whole process of finding people, um, and, uh, And making sure everything is collected.

Um, uh, I think that’s, that’s something we can really support them. Uh, I think there are some, some sort of systems out there, but generally our companies have their, um, have quite old, um, and, um, uh, legacy HR systems and, um, you know, we can use. Uh, we can use the bots to, to help them. There was everything around these legacy HR systems, uh, for example, aggregating CVS, um, collecting assessment results, um, and interview notes.

And we can put this all in the right places in the HR system, because ideally we need to document most of the stuff we do with our recruits and. Yeah, we need to, we need to have all that information available so we can, we can also act on GDPR and all that stuff. So yeah, the belt can help us, um, to, to make, uh, to make.

Yeah, it’s mainly to fill the gaps, um, uh, of, uh, of these, uh, old HR systems. Yeah. And, um, you know, you talk about HR and I think another important use case is, um, of course, um, employment, history, verification, and, um, you know, obviously that process. Um, has got numerous routines and steps, you know, such as I dunno, a Ray arranging interviews and, you know, everything that, that follows up from that.

And also, um, you know, maintaining the records, um, of, of, um, that we verify this, this employee, their previous, um, employer and, um, you know, All of that can be drastically reduced using RPA and stringing that process together and automating that process. Um, a recent study done by UI path, um, where they, they, they provided a case study and they, they rolled out our automation program, you know, within sight, this use case, um, and roughly over eight weeks.

And they calculated that they reduced, um, around about 4,000. Of the manual labor that went into these activity. So, which is, which is a very impressive, um, you know, uh, reduction, you know, in, in, in, in, in, in the sort of, uh, the time it takes, um, you know, for, for, for this recruiting process. Yeah, I think, um, uh, there are so many use cases on the chatbot side we recently covered, uh, just on the HRS, uh, I dunno, 40 different use cases.

And we see maybe some, some very similar, uh, candidates here where, where RPA can jump in, uh, and to. They’re hiring onboarding and headcount reduction. So these are very typical use cases, especially for growing or shrinking firms, unfortunately. Um, uh, since, since, since the pandemic. So yeah. Um, shrinking firms hiring and firing is, uh, is significant, um, uh, in terms of workload for HR.

And, uh, and everyone who is supporting them, uh, yeah. As well, the it departments and facility management. So, so all these things and, uh, off of the process, um, uh, can be quite costly. Um, and then putting, putting this in sort of solutions. Um, yeah, I think, uh, RPA. Can it can be, again, the glue between all these different things can streamline the process.

And I think the big benefit of RPAs is can do that very quickly. So instead of putting lots of solutions in there, um, uh, big, big systems who, uh, which, which cover all these areas with RPA, we will, can really see fast, fast results. Uh, I think was the most RPA platforms. Use low code. So that helps us as well to get these solutions already defined very, very quickly.

So yeah, by automating, um, uh, these kinds of processes, hiring, onboarding, and head count reduction, I think, um, you know, you can, can really speed up the whole process and, um, you know, free up again. The typical, the typical one free up time within, within these department. Yeah. And of course, once you’re onboarded your employees, um, then it’s the sort of typical run of the mill processes that you have to do periodically and, you know, and that includes payroll automation.

Now there’s a lot of software out there that does. The automation of payroll. Um, but there’s always going to be gaps where you have to transfer data from one system to another system. And typically what people do is they do that using Excel spreadsheets and, you know, Mirage of other type of tools. So I think with.

For, if you look at payroll automation in general, you know, RPA is a very, very good way that you can actually increase the automation within scientists’ payroll management process, you know, by sorting information, running those processes, and also ensuring the accuracy. And, you know, this is all sort of true for, for other types of, um, processes with insights, um, HR, for instance, absence management, you know, where this absentees.

Uh, you know, either to vacations or, um, you know, or, you know, all of these things that, um, as a member of staff is not within inside your business, how does that process look like? What is the types of systems that you need to actually interact with to log the absence and manage that? And, you know, I think, uh, a lot of businesses out there probably have.

Various places, maybe a core HR system. But again, I think RPA is just one of those technologies that bring all of that stuff together into a single process. You know, we, we look at things like workers’ compensation claims, and again, You know, there might’ve been an injury at work, um, or illness needs to be reported.

And, um, you know, there could be a claims, uh, investigation that that happens, um, you know, for, for, for compensation claim, for example. So again, uh, quite a complicated set of activities that needs to happen, but very standard, um, You know, very easy to, to, to actually describe. Um, and you know, RPA is a really, really.

Uh, technology to, to, to automate that. And if we look at things like expense management, for example, again, the same thing where you might have an expense system, or you might not have one, but either way, you know, you could use the RPA bot to, to, to, to sort of, um, you know, source the data. From, uh, an expense submission, um, you know, perhaps, uh, send an automated email to somebody that needs to approve it, or if it’s part of a bigger workflow, but really just kind of be like you said, such a dark blue that actually brings things together in terms of providing that nice end to end process experience.

Absolutely. Yeah. And, um, I think to, to wrap, to wrap up, um, on, on, on the, um, HR use cases, we discussed this in a, in this other, um, episode all about, um, um, chat bot use cases. So it was a, I RPA we have the opportunity to put a, um, um, Uh, an HR virtual assistant, uh, in place for our business. And we can then allow our staff to, to.

Communicate with the chat bot for lots of these things. Um, we just went through and then, um, the chat bot will then do the communication and behind the scenes, uh, um, through RPA, maybe an into an old expense management system into an old claims management system, into the old legacy HR system. But, um, Through this virtual assistant can be a quite engaging conversation.

They can ask questions, they can book days off, um, and all through this, um, chat bot, um, channel. And, um, yeah, it’s, it’s a very, very exciting topic in general and it’s growing. Um, so, so the combination chat bot and RPA is definitely something to look at. Um, And, uh, yeah. So if you have your RPA processes already implies, or you’re thinking about this also think about chatbots.

Definitely. And I think that’s, I think that’s a, that’s a lot for, for one session. Um, uh, I’m sure we will cover far more. Um, use cases, please submit your ideas on our website, the automation Um, we always looking, looking out for great ideas, um, to talk about, um, and, uh, you’re if you have a specific area like operations or so you’d like to learn more about use cases in that field.

Or maybe in finance or specifically in financial services and banking. So there’s so much more we can, we can cover our logistics, I think. Yeah. So there are plenty, plenty of use cases and, um, yeah, let us know. Hopefully you could take a few points away, um, and, um, maybe. Um, jumped straight into, into action.

Um, yeah, just feel free to reach out to, to, to myself, uh, get a trial and then we can get you and get you, get you going very quickly. Um, yeah, so I think that will be it for today. Thank you so much for listening. Let’s automate.

That’s it again with this episode of the process in automation podcast. If you liked this episode, please give us a five-star rating and don’t forget to subscribe to this podcast. So you don’t miss any upcoming episode. We hope you will tune in next time. Until then let’s automate.

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